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Coeli M. Hoover, Northern Research Station, US Forest Service, Durham, NH
Presenting Author(s)
Coeli M. Hoover
Northern Research Station, US Forest Service Durham, NH, USA
Background/Question/Methods The US Forest Service’s Forest Inventory and Analysis Program (FIA) is the nation’s forest census and is responsible for collecting a wide variety of data that describes the state of US forests. FIA employs a standardized sampling design using a systematic grid of plots across all lands. Data are collected yearly on a subset of plots in each state; plots are remeasured approximately every 5-7 years in the East and 10 years in the West. While many natural resources practitioners have a basic understanding of the FIA program and the type of data collected, most casual users are unlikely to be familiar with the breadth of information available and the many potential uses of the data. National Forest System personnel are tasked with a broad range of management objectives, from wildlife habitat and recreation to sustainable timber production and forest health, resulting in extensive information needs. Working together, managers and researchers can harness the power of the FIA database to transform data into the information required to support management objectives. We highlight examples of scientists and managers putting FIA data into action on forested landscapes in the northeastern and midwestern United States. Results/Conclusions We present case studies encompassing a variety of management objectives. In Maine and New Hampshire, information collected on standing dead trees was employed to estimate availability of potential roost trees in the evaluation of the Northern Long-eared bat as a candidate for listing as a threatened or endangered species. In the Allegheny hardwood region of Pennsylvania and New York, data from an expanded FIA plot network was used to investigate the decline in health of black cherry, an important species in the region, and uncover potential causes. The exact location of FIA plots is confidential because plots are located on private as well as public lands. On the Ottawa National Forest in Michigan, FIA plots were mapped to different management areas in a manner that preserved confidentiality, allowing managers to develop metrics characterizing vegetation condition, a key step in revising the forest monitoring plan. In the oak-hickory forests of Ohio, FIA data enabled managers to supplement local measurements, expand coverage, and train a model used to predict oak habitat suitability. In these examples, the element critical to success was collaboration between managers who identified information needs, and researchers who developed techniques to put the power of the FIA dataset into action to meet those needs.
